Flaws due to race conditions in which the binding of a name to an object changes between repeated references occur in many programs. We examine one type of this flaw in the UNIX operating system, and describe a semantic method for detecting possible instances of this problem. We present the results of one such analysis in which a previously undiscovered race condition flaw was found.

This thesis examines the issues relating to non-discretionary access controls for decentralized computing systems. Decentralization changes the basic character of a computing system from a set of processes referencing a data base to a set of processes sending and receiving messages. Because messages must be acknowledged, operations that were read-only in a centralized system become read-write operations. As a result, the lattice model of non-discretionary access control, which mediates operations based on read versus read-write considerations, does not allow direct transfer of algorithms from centralized systems to decentralized systems. This thesis develops new mechanisms that comply with the lattice model and provide the necessary functions for effective decentralized computation. Secure

Abstract. We argue that there is currently no satisfactory general framework for comparing the extensional computational power of arbitrary computational models operating over arbitrary domains. We propose a conceptual framework for comparison, by linking computational models to hypothetical physical devices. Accordingly, we deduce a mathematical notion of relative computational power, allowing the comparison of arbitrary models over arbitrary domains. In addition, we claim that the method commonly used in the literature for “strictly more powerful” is problematic, as it allows for a model to be more powerful than itself. On the positive side, we prove that Turing machines and the recursive functions are “complete ” models, in the sense that they are not susceptible to this anomaly, justifying the standard means of showing that a model is “hypercomputational.” 1

INTRODUCTION TO POS: A PROTOCOL OPERATIONAL SEMANTICS JEAN-LUC KONING Leibniz-Esisar, 50 rue de Laemas - BP 54 26902 Valence cedex 9, France PIERRE-YVES OUDEYER Sony CSL Paris, 6 rue Amyot 75005 Paris, France Received (to be inserted Revised by Publisher) In this paper we propose a system for representing interaction protocols called POS which is both Turing complete and determine a complete semantics of protocols. This work is inspired by the Structured Operational Semantics in programming languages. We precisely dene POS and illustrate its power on an extended example. Keywords: interaction protocols, operational semantics, inter-agent communication, collaboration, information agents. 1. Introduction Multiagent systems are based on the idea that by gathering simple autonomous systems (agents) in a society and endowing them with interaction capabilities, such a society can display comple

We report on the programming system eb that supports computational science and engineering. eb has the constructive philosophy begun by Bishop. This philosophy is explained in enough detail to show how this view is acceptable to, but different from, -calculus and Martin-Lof theories. eb raises a theoretical question of semantics: how to guarantee that the language as implemented works as intended by the constructive reals model? The eb system is currently in "bootstrap" mode. We discuss the implementation of this bootstrap as well as plans for the future. This implementation is a source to source translator to C. Primitive types in eb are multiprecision integers and floating point. As innovations, eb supports both functional and relational models, is nondeterministic, and uses failure as a control mechanism. Keywords Numerical programming (computational science and engineering), functional logic programming. Word Count 4999. 1 Introduction "The life which is unexamined is not wo...

. The goal of foundational thinking in computer science is to understand the methods and practices of working programmers; we might even be able to improve upon those practices. The investigation outlined here applies the methods of constructive mathematics 'a l`a A. N. Kolmogoroff, L. E. J. Brouwer and Errett Bishop to contemporary computer science. The major approach is to use Kolmogoroff's interpretation of the predicate calculus. This investigation includes an attempt to merge contemporary thoughts on computability and computing semantics with the language of mental constructions proposed by Brouwer. This necessarily forces us to ask about the psychology of language. I present a definition of algorithms that links language, constructive mathematics, and logic. Using the concept of an abstract family of algorithms (Hennie) and principles of constructivity, a definition of problem solving. The constructive requirements for an algorithm are developed and presented. Given this framewor...

Is there a physical constant with the value of the halting function? An answer to this question, as holds true for other discussions of hypercomputation, assumes a fixed interpretation of nature by mathematical entities. We discuss the subjectiveness of viewing the mathematical properties of nature, and the possibility of comparing computational models having different views of the world. For that purpose, we propose a conceptual framework for power comparison, by linking computational models to hypothetical physical devices. Accordingly, we deduce a mathematical notion of relative computational power, allowing for the comparison of arbitrary models over arbitrary domains. In addition, we claim that the method commonly used in the literature for “strictly more powerful ” is problematic, as it allows for a model to be more powerful than itself. On the positive side, we prove that Turing machines and the recursive functions are “complete ” models, in the sense that they are not susceptible to this anomaly, justifying the standard means of showing that a model is more powerful than Turing machines.

.51> zero(x) j 0 2. successor: defined by succ(x) j x + 1 3. projection: defined by proj n k (x 1 ; : : : ; xn ) j x k and two basic operators for constructing new functions: 1. composition: denoted by h k = comp( f n ; g k 1 ; g k 2 ; : : : ; g k n ) 2. primitive recursion: denoted by h n+1 = prec( f n ; g n+2 ) Here all arguments are natural numbers and the superscripts on the functions f , g, and h denote their "arities"; that is, the number of arg

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